Keynote Presentations

Keynote Speaker

Topic

Prof. Guanrong (Ron) Chen
City University of Hong Kong

Pinning Controllability of Complex Dynamical Networks

Shu-Ching Chen, Ph.D.
School of Computing and Information Sciences
Florida International University, Miami, FL 33199, USA IEEE Fellow

Emerging Multimedia Big Data Research

Prof. Pau-Choo Chung
Department of Electrical Engineering, National Cheng Kung University
IEEE Fellow

Inertial Sensors Analysis for Healthcare Applications

Prof. Feng Gao
Xi’an Jiaotong University, China

Energy and Production Cooperated Scheduling in Energy Intensive Enterprise

Prof. Hongwei Ma
Xi’an University of Science and Technology, Xi’an, China
CMES Senior Member

Defect Electromagnetic Signal Noise Reduction by Combination of Wavelet and EMD for Steel Cord Conveyor Belt

Prof. Guanrong (Ron) Chen
City University of Hong Kong

Topic: Pinning Controllability of Complex Dynamical Networks

    This talk will firstly review the notion of pinning control for complex dynamical networks and then discuss in detail the structural controllability and state controllability of networked MIMO (multi-input/multi-output) LTI (linear time-invariant) dynamical systems, showing some interesting counterintuitive examples, with necessary and sufficient conditions presented.

About the Speaker:

   Professor Chen has been a Chair Professor and the Director of the Centre for Chaos and Complex Networks at City University of Hong Kong since 2000, prior to that he was a tenured Full Professor at the University of Houston, Texas, USA. He was elected IEEE Fellow in 1997 and received the 2011 Euler Gold Medal from Russia and the State Natural Science Awards of China in 2008 and 2012, respectively. In addition, he was conferred Honorary Doctor Degrees by the Saint Petersburg State University, Russia in 2011 and by the University of Normandy, France in 2014. Furthermore, he was elected a Member of the Academy of Europe in 2014 and a Fellow of The World Academy of Sciences in 2015. He is a Highly Cited Researcher in Engineering as well as in Mathematics according to Thomson Reuters.

Shu-Ching Chen, Ph.D., IEEE Fellow
Eminent Scholar Chaired Professor
School of Computing and Information Sciences
Florida International University, Miami, FL 33199, USA
Email: chens@cs.fiu.edu
http://www.cs.fiu.edu/~chens

Topic: Emerging Multimedia Big Data Research

    The pervasiveness of mobile devices & consumer electronics and the popularity of Internet & social networks have generated huge amounts of multimedia information in various media types (such as text, image, video, and audio) shared among a large number of people. This creates the opportunities and intensifies the interest of the research community in developing methods to address multimedia big data challenges for real-world applications. Providing solutions to multimedia data such as images and videos brings about a higher level of difficulties at attempting to understand their semantic meaning. In this talk, I will discuss the research opportunities and challenges in multimedia big data, and introduce a coherent framework for multimedia big data management and retrieval, ranging from multimedia data processing to indexing, query, retrieval, and presentation. A set of core techniques, such as multimedia big data analysis, content-based image/video retrieval, and multimedia data mining, will be discussed in details and demonstrated using a prototype system. In addition, I will present the idea of applying these techniques to practical applications such as disaster information management.

About the Speaker:

    Dr. Shu-Ching Chen is an Eminent Scholar Chaired Professor in Computer Science in the School of Computing and Information Sciences (SCIS), Florida International University (FIU), Miami. He received his Ph.D. in Electrical and Computer Engineering from Purdue University, West Lafayette, IN, USA in 1998. He is the Director of Distributed Multimedia Information Systems Laboratory and Co-Director of the Integrated Computer Augmented Virtual Environment (I-CAVE) at SCIS. His main research interests include multimedia big data, content-based image/video retrieval, distributed multimedia database management systems, multimedia data mining, and disaster information management. Dr. Chen has authored and coauthored more than 300 research papers and four books. Dr. Chen has been the PI/Co-PI of many research grants from NSF, National Oceanic and Atmospheric Administration (NOAA), Department of Homeland Security, Army Research Office, Naval Research Laboratory (NRL), Florida Office of Insurance Regulation, IBM, and Florida Department of Transportation with a total amount of more than 26 million dollars.
Dr. Chen was named a 2011 recipient of the ACM Distinguished Scientist Award. He received the best paper award from 2006 IEEE International Symposium on Multimedia. He was awarded the IEEE Systems, Man, and Cybernetics (SMC) Society’s Outstanding Contribution Award in 2005 and was the co-recipient of the IEEE Most Active SMC Technical Committee Award in 2006. He was also awarded the Inaugural Excellence in Graduate Mentorship Award from FIU in 2006, the University Outstanding Faculty Research Award from FIU in 2004, the Excellence in Mentorship Award from SCIS in 2010, the Outstanding Faculty Service Award from SCIS in 2004 and 2014, and the Outstanding Faculty Research Award from SCIS in 2002 and 2012. He has been a General Chair and Program Chair for more than 55 conferences, symposiums, and workshops. He is the founding Editor-in-Chief of the International Journal of Multimedia Data Engineering and Management, and Associate Editor/Editorial Board of IEEE Multimedia, IEEE Trans. on Human-Machine Systems, and other 13 journals. He served as the Chair of IEEE Computer Society Technical Committee on Multimedia Computing. He is Co-Chair of IEEE Systems, Man, and Cybernetics Society’s Technical Committee on Knowledge Acquisition in Intelligent Systems. He was a steering committee member of the IEEE Transactions on Multimedia. He is a fellow of IEEE and SIRI.

Prof. Pau-Choo Chung
Department of Electrical Engineering, National Cheng Kung University
IEEE Fellow

Topic: Inertial Sensor Based Wearable Devices for Healthcare Applications

    Despite the fact that the concept of using long-term personal records has been well recognized for decades, sparse patient physical exam records are still the main base for disease diagnosis and treatment. One of the main reasons for this is the lack of devices and systems for effectively collecting personal data and turning the data into health-meaningful information.
The current development of wearable devices with IoT presents a huge potential for fulfilling the needs of long-term data collecting and enabling patients to be monitored in real-time. Among all the signals, activities show as one essential indicator to the physical status of the elderly. In this talk, we will focus on the introduction of the inertial sensors based wearable devices for motion analysis and their applications to healthcare. Methods for turning the measured inertial signals into information for better understanding the elderly situation will also be presented. Several potential clinical applications will also be introduced.

About the Speaker:

    Pau-Choo (Julia) Chung (S’89-M’91-SM’02-F’08) received the Ph.D. degree in electrical engineering from Texas Tech University, USA, in 1991. She then joined the Department of Electrical Engineering, National Cheng Kung University (NCKU), Taiwan, in 1991 and has become a full professor in 1996. She served as the Head of Department of Electrical Engineering(2011-2014), the Director of Institute of Computer and Communication Engineering (2008-2011), the Vice Dean of College of Electrical Engineering and Computer Science (2011), the Director of the Center for Research of E-life Digital Technology (2005-2008), and the Director of Electrical Laboratory (2005-2008), NCKU. She was elected Distinguished Professor of NCKU in 2005 and received the Distinguished Professor Award of Chinese Institute of Electrical Engineering in 2012. She also served as Program Director of Intelligent Computing Division, Ministry of Science and Technology (2012-2014), Taiwan.
Dr. Chung participated in many international conferences and society activities.
She served as the program committee member in many international onferences, such as the Publicity Co-Chair of WCCI 2014, SSCI 2013, SSCI 2011, and WCCI 2010. She served as an Associate Editor of IEEE Transactions on Neural Network and Learning Systems(2013-2015) and currently is serving as the Associate Editor of IEEE Transactions on Biomedical Circuits and Systems.
Dr. Chung was the Founding Chair of IEEE Computational Intelligence Society (CIS) Tainan Chapter(2004-2005). She was the Chair of the IEEE Life Science Systems andApplications Technical Committee (2008-2009). She was a member in BoG of CASSociety (2007-2009, 2010-2012). She served as an IEEE CAS Society DistinguishedLecturer (2005-2007) and the Chair of CIS Distinguished Lecturer Program(2012-2013). She served on two terms of ADCOM member of IEEE CIS (2009-2011,2012-2014), the Chair of IEEE CIS Women in Engineering (2014). She is a Memberof Phi Tau Phi honor society and is an IEEE Fellow since 2008. Currently she isserving as the Vice President for Members Activities of CIS.

Prof. Feng Gao
Xi’an Jiaotong University, China

Topic: Energy and Production Cooperated Scheduling in Energy Intensive Enterprise

    With the intensification of global energy and environment crisis, energy conservation and emissions reduction has become one of the focuses of human society. Energy intensive enterprise (EIE, e.g. iron and steel, electrolytic aluminum) as a large energy consumption, is playing an important role in relieving the energy shortage problem. Electricity is indispensable in production processes of an EIE, and electricity cost account for a large proportion of the total cost of production of an EIE. Electrical energy scheduling can help an EIE reduce its electricity costs and/or improve its energy utilization, where electrical energy scheduling refer to schedule electrical energy related devices in an EIE. In addition, with the development of Smart Grid and renewable energy application, the new approaches are introduced to solve the energy system and production system coordination optimization scheduling problem for EIE.
Firstly, based on characteristics of electrical energy systems in EIEs (electricity system in an EIE usually is coupled with production process and other energy systems), the author focuses on electrical energy scheduling of EIEs under the perspective of demand response without considering the uncertainties. Then, the author studies the energy system and production system coordination optimization scheduling problems with random factors: by-produce gas and electricity power transformation and optimization configuration problem, and self-balance between self-generation and electricity consumption with uncertainties, and self-generation schedule with wind power under uncertainties. In addition, because of the uncontrollable and stochastic feature, it is a significant challenge to maintain the reliability of high renewable energy penetration system. Energy storage can provide more flexibility of renewable generation and decrease the impact of enterprise micro-grid on utility grid. One of the most important decisions in system design level is the optimal storage capacity, since storage cost will still be expensive in the near future. Storage sizing problem for high renewable penetration micro-grid is also discussed. eonveyor belt.

About the Speaker:

    Prof. Feng Gao received his B.S in automatic control from Xi’an Jiaotong University, China in 1988, and his M.S. and Ph.D. in systems engineering from the same university in 1991 and 1996. He is currently a professor at Systems Engineering Institute, Xi’an Jiaotong University. He is also a Vice Director of the State Key Lab for Manufacturing Systems from 2009, and the Vice Dean of School of Electronic and Information Engineering from 2016, Xi’an Jiaotong University. He visited Harvard University as a postdoc from Feb. 2000 to Jun. 2001. His research interests include intelligent control, machine learning, power system optimization, scheduling and prediction. He is the member of IEEE from 2005. He was granted the second prize of the national natural science awards of China in 2005.

Prof. Hongwei Ma
Xi’an University of Science and Technology, Xi’an, China
CMES Senior Member

Topic: Defect Electromagnetic Signal Noise Reduction by Combination of Wavelet and EMD for Steel Cord Conveyor Belt

    In order to eliminate the defect electromagnetic signal noise of the steel cord conveyor belt used in coal mine, a new noise reduction method of non-stationary electromagnetic signal by combination of the improved threshold wavelet and Empirical Mode Decomposition(EMD) is proposed. Firstly, the improved threshold wavelet denoising method is used to reduce the noise of the defect electromagnetic signal obtained by an electromagnetic testing system. Then the EMD method is used to decompose the denoised signal and the effective Intrinsic Mode Function(IMF) is extracted by the dominant eigenvalue method. Finally, the signal reconstruction based on IMF is carried out. In order to verify the proposed noise reduction method, the comparative tests with the traditional wavelet method are carried out for the defective joint and rope break cases. The experimental results show that the proposed method in this paper obtains the higher Signal to Noise Ratio(SNR) for the defect electromagnetic signal noise reduction of steel cord conveyor belt.

About the Speaker:

    Hongwei Ma, Ph.D., professor, doctoral tutor, vice president of Xi'an University of Science and Technology. His main research directions include: intelligent detection and control, industrial robot, mechanical and electrical integration technology, intelligent coal mine machinery, etc.. Prof. Ma had completed many projects funded by the National Natural Science Foundation of China and many provincial and ministerial level projects. Prof. Ma had won 3 provincial and ministerial level scientific and technological awards, more than 20 national invention patents and utility model patents, published more than 110 academic papers, and more than 50 articles were retrieved by SCI, EI, ISTP, etc., and cultivated more than 60 graduate students.

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